Machine Learning Software Engineer (Match Group AI)

Match Group AI Team Introduction Match Group AI (MG AI) is the central tech organization that drives innovation across Match Group’s global portfolio, including Tinder, Hinge, Azar, Pairs, Match, BLK, etc. Our mission is to solve the most complex challenges in online dating (e.g., Recommendation, Trust & Safety, Profile Enhancement) by bridging cutting-edge AI research with excellent software engineering. Unlike brand-specific teams (e.g., Tinder, HYPERCONNECT AI), MG AI team offers the unique opportunity to impact the entire Match Group ecosystem. You won't just build for one app; we aim to develop scalable AI solutions that power Tinder, Hinge, and beyond, defining the technological gold standard for the global dating industry. Detailed article: Introduction to Match Group AI Team (written in Korean) Working as a MLSE at MG AI While ML Engineers focus on modeling, Machine Learning Software Engineers (MLSEs) at MG AI team focus on the critical bridge between research and production. We ensure that state-of-the-art models (including LLMs and Multimodal systems) are integrated into high-traffic environments, serving millions of users in real-time. We also upload a selection of interesting problems solved by our team's engineers to the Hyperconnect Tech blog (written in Korean). On-device AI Face Verification Pipeline Optimization 10 Python Performance Optimization Tips for High-Performance ML Backends

• Bridge Research to Production: Operationalize complex ML models into robust, scalable features for global brands like Tinder and Hinge. • Build ML Services: Design and develop backend services and distributed systems that enable the seamless consumption, scaling, and monitoring of ML models. • Build ML Pipelines: Design and develop ML serving pipelines (real-time and batch) to deliver model outputs with low latency and high reliability. • Drive LLM Innovation: Partner with ML engineers to deploy and optimize Large Language Models (LLMs) for practical, high-impact use cases such as profile assistance. • Co-Engineering with Brands: Engage in deep technical collaboration with engineering counterparts (Tinder, Hinge, Azar, Pairs, etc.) across various global offices, including Seoul, Palo Alto, LA, Vancouver, Dallas, and Tokyo.